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Websites
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http://jwegan.com
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http://github.com/jwegan
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Articles by John
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AMP In Email And What It Means For The Future of Email Marketing
AMP In Email And What It Means For The Future of Email Marketing
It is not often that something new comes along in the email space, much less something that has the potential to change…
47
5 Comments -
All the Advice You’ve Read on Push Permission Prompts is WrongJan 9, 2018
All the Advice You’ve Read on Push Permission Prompts is Wrong
For the last few years, it has become a widely promoted industry best practice to have pre-prompts for iOS’s push…
40
1 Comment -
One Simple Logic Error That Can Undermine Your Growth StrategyMar 15, 2017
One Simple Logic Error That Can Undermine Your Growth Strategy
Survivorship bias is one of the easiest logical errors to make in Growth. If you’re not familiar with survivorship…
295
12 Comments -
The Wrong Way To Analyze ExperimentsNov 17, 2016
The Wrong Way To Analyze Experiments
One of the biggest mistakes I see Growth teams make when it comes to analyzing experiments is focusing too much on…
63
6 Comments -
How Pinterest Increased Active Users With One Simple TrickMar 21, 2016
How Pinterest Increased Active Users With One Simple Trick
For many areas of growth, presenting your message with the right hook to pique a user’s interest and to get them to…
337
11 Comments -
4 Steps To Develop Your Push Notification StrategyFeb 2, 2016
4 Steps To Develop Your Push Notification Strategy
Startups often struggle with how to develop their push notification strategy. While email has been around for decades…
151
7 Comments -
Experiment Segmentation: Avoiding Old Dogs and Watered Down ResultsDec 1, 2015
Experiment Segmentation: Avoiding Old Dogs and Watered Down Results
One of the biggest growth bets we placed during my time at Shopkick was on geofenced notifications. Geofenced…
101
1 Comment -
When Do Features Drive Growth: A Case StudyJul 22, 2015
When Do Features Drive Growth: A Case Study
As I mentioned in my previous post, I often see this belief in product development that adding new product features to…
76
6 Comments -
How Can Reddit Solve its Growth Problem?Jul 14, 2015
How Can Reddit Solve its Growth Problem?
Reddit has been undergoing a lot of turmoil lately. CEO Ellen Pao resigned ostensibly because she felt she couldn’t…
87
10 Comments -
Why You Should Be A/B Testing Your InfrastructureApr 3, 2015
Why You Should Be A/B Testing Your Infrastructure
The benefits of using a data-driven approach to product development are widely known. Most companies understand the…
41
2 Comments
Activity
10K followers
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John Egan shared thisWe've grown a lot this year and have heard the complaints about rate limits. I'm excited that with this compute partnership with SpaceX effective immediately we are doubling Claude Code 5 hour rate limits across all plans, and removing peak hour limits on Pro/Max. https://lnkd.in/g9Hme_73Higher usage limits for Claude and a compute deal with SpaceXHigher usage limits for Claude and a compute deal with SpaceX
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John Egan reposted thisJohn Egan reposted thisSay hello to Opus 4.7, our most capable Opus model yet! Two things I'd say about the model: 1) It's much more rigorous on long-running tasks Far better than Opus 4.6 on following instructions and verifying it's own outputs. Can really hand off hardest work with very little supervision. 2) It's vision is a lot stronger Opus 4.7 can see images at more than 3x the resolution, which lets it create much higher quality UI, slides, docs etc. It's live on our API, Claude Code, Cowork, and Claude chat. Enjoy :)
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John Egan shared thisIf you're considering switching to Claude from another AI platform you can now import your memories in under a minute. https://lnkd.in/geiNu__N
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John Egan reposted thisJohn Egan reposted thisClaude is #1 in the U.S. App Store 🔥 In AI, 2026 is the year of the choice. In the social media era, I always felt like as an end-user, I had no agency. All the companies had basically the same policies, prioritizing profit above all else. If I wanted to vote with my feet, I had nowhere to go. Today, at a time when people have mixed feelings about AI seeming inevitable and as something “happening to them”, we believe people deserve a choice. We strive for Anthropic to represent a better choice, even if it comes at significant cost to us. Our overarching princples are that we want to ensure that powerful AI remains safe and beneficial to humanity. We want Claude to expand your thinking, and not exploit you or your attention. We are keeping Claude ad-free, and resisting leaning into AI slop. We are against the use of Claude for domestic mass surveillance of Americans, and fully autonomous weapons. This is what we stand for. It is coming at great cost to us, but we are united as a company in fighting for what we believe in. Unlike in previous eras, consumers today have a choice. They have a choice in what they believe AI companies should stand for. They have a choice in what they want the future of America, and the future of our entire planet, to shape out to be. We are grateful that the choice that consumers are making is Anthropic. We take your faith in us very seriously, and will do everything in our power to shape a better future for us all.
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John Egan shared this“No amount of intimidation or punishment from the Department of War will change our position on mass domestic surveillance or fully autonomous weapons.” https://lnkd.in/gHvkDfzYStatement on the comments from Secretary of War Pete HegsethStatement on the comments from Secretary of War Pete Hegseth
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John Egan reposted thisJohn Egan reposted thisA statement on the comments from Secretary of War Pete Hegseth: https://lnkd.in/e-guCny5
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John Egan shared thisWe’re growing the Growth team at Anthropic across PM, Design, and Engineering! The growth team uses product led growth tactics to help scale users & revenue across Anthropic’s portfolio of products and help deliver safe trustworthy AI into the hands of millions of users. If you’re interested in the opportunity to have a massive impact, check out the job descriptions below 👇 Full-stack Growth Engineer: https://lnkd.in/g4X2jRq3 Growth Product Designer: https://lnkd.in/g_UMhARi PM Claude Code Growth: https://lnkd.in/g8ApbzpK
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John Egan shared thisClaude Opus 4.5 drops today. 80.9% on SWEBench making it the best model in the world for coding. Give it a try on Claude Code.
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John Egan shared thisIf you haven't given Claude a try yet, you can get 1 month of Pro for free if you signup using your company email. Promotion is for today only ⏱️! Use it to try some of our most popular features: Claude Code, Skills, etc https://lnkd.in/gcvu4AJX
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John Egan liked thisJohn Egan liked thisOpus 4.8 is out 💡 It’s our smartest Opus model to date, and the best GA model for coding and agents. Benchmarks are great, but IMO the behavior change is a much bigger deal. Opus 4.8 plans before it edits, recovers from its own errors, and finds creative ways around obstacles instead of stalling. Feels much more like a senior engineer than 4.7, and is also better at long-horizon work. Other things that we’re shipping today: 1) Fast mode for Opus 4.8 - same model at roughly 2.5x the speed, and 3x cheaper than before 2) Dynamic workflows in Claude Code - runs hundreds of parallel subagents in a single session, and verifies the work before reporting back 3) Claude.ai effort controls - can now choose how much effort Claude puts into a response on claude.ai Same price as 4.7, so it's a drop-in upgrade. Excited to see what 4.8 unlocks for y’all :) https://lnkd.in/g7U9HsTY
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John Egan reacted on thisJohn Egan reacted on this[UPDATE] Culprit Identified! As the phantom burn stopped this morning, I was able to ask Claude to self diagnose and it looks like memory was involved, but not the official memory plugin but a third party tool I used from the marketplace (claude-mem@thedotmack). This plugin runs a persistent background observer agent that watches the entire session and makes API calls to generate memory. It runs from login to logout with no visible indicator in the UI. In my case, the observer's session file had grown to 200MB+, meaning every single API call was loading that entire context. The cost never showed up as user-initiated usage, and the oversized file even blocked the /status breakdown from computing who was responsible. That's what actually led me to digging there. HUGE thanks for all the folks at Anthropic for jumping on this so quickly - John Egan. Sagnik Ghosh, Fiona Fung, Boris Cherny, Ami Vora! And thanks everyone else for tagging folks :) Wonder if some of the following features may make sense for CC for similar challenges. I know the bane of supporting third party code without owning it. * Surface active background/plugin subagents in /status * Require marketplace plugins to declare if they spawn API-calling background agents? Similar to Android Permissions? * Alert users when usage spikes without a user-initiated message in /status or when sessions usage goes past 50% * Per-plugin usage accounting in the breakdown (in this case it would have helped diagnose the issue pretty quickly) [ORIGINAL] Hey Folks at Anthropic, I have found what seems like either a bug in usage tracking, or potentially a breach in how my Pro subscription can be used by third party to generate usage, or a rogue feature eating credits/tokens without me doing anything, or a stuck process -- anyways definitely not on my end afaict. I noticed since yesterday my 5h usage is stuck at 100%, despite the usage window refreshing. This morning I patiently waited until 8.30am hits for new usage window to open and was able to see my usage growing really fast without actually doing anything in either claude code or on any other Claude surfaces. As a matter of fact at 8.30am sharp, it was already 10% 5h usage. I used help bot to document before/after but the help bot is pretty useless here tbh. What is a way to escalate this please and investigate? My account/subscription is de facto unusable and burns credits without me doing anything. It also impacts my weekly limit. Some images to document. I feel frustrated, doubly so as i have Codex chugging along all night in another window without a blip...
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John Egan reacted on thisJohn Egan reacted on thisExcited to make my first post and share that Weights has been acquired by OpenAI. Over the past few years, we built Weights.com, Voyages, Replay, and a family of AI products used by millions of creators and the world’s top artists. I’m incredibly proud of what our team built, and grateful to everyone who created with us, invested in us, and supported us along the way. We started Weights to build the products we believed should exist at the forefront of AI. I’m excited to bring that experience to OpenAI, where JonLuca DeCaro and I will be leading Emerging Products. See y’all back here for the next one 🫡
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John Egan liked thisJohn Egan liked thisIt was such a privilege to sit down with Oprah Winfrey to discuss everything from Anthropic’s public benefit mission to our commitments on privacy and child safety. Unsurprisingly, she asked great questions: putting individuals, families, and the human experience at the center in the way only she can. At Anthropic we talk about the importance of holding light and shade. Achieving the best kind of AI future - the type of future humanity deserves - involves wrestling constantly with the complexity of this moment and working tirelessly to do good things well. A huge thank you to Oprah for the conversation and for keeping the focus on that future. If you’d like to watch the full interview, you can find it here: https://lnkd.in/gUd_rT65
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John Egan reacted on thisExcited to start sharing more about what I've been working on... Rebuilding community starts with spending less time on our phones and more time in person with one another. We're building a Quality Time Machine - an analog gaming console that brings the magic back to game night. While we're still early, I'm confident at this point that we have created something truly magical. More to come soon, follow along to learn more!John Egan reacted on thisThe Quality Time Game Company’s mission is to improve the time we spend together by bringing table-top gaming into the future. We have cherished memories of game nights with family and friends. But today those games are collecting dust in the closet while most of us stare at our phones. We don’t just love playing games, we love playing games together. And we want future generations to treasure that experience, too. We appreciate the benefits of technology, but our world often feels like it’s serving big-tech billionaires and engineers who mine our time efficiently for their profit. Scrolling, liking, and subscribing will never create lifelong friendships, meaningful memories, or build community. We are artists and we’re taking a different approach. We’re building Analog Gaming Consoles that create personalized table-top games. We’re using AI to bring out the best in us humans - time spent face to face, laughing, being creative, learning, and celebrating our playfulness - tech to help reflect humanity at its best. We want every game night to be one to remember. We’re not a tech company, an AI company,�� or a blockbuster studio. We’re not a non-profit, either. We just don’t believe making a buck requires selling out humanity. Fun Up, Phones Down, Any Questions! ------The Quality Time Game Company-----
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John Egan liked thisJohn Egan liked thisFarewell Pinterest, Hello Roon 👋 📌 🩺 One month into a new chapter, I want to take a moment to reflect on my journey so far. After 13 incredible years at Pinterest, the time felt right for a new adventure. I am thrilled to share that I have joined the team at Roon as the Director of Design. My decade-plus at Pinterest was an unforgettable chapter where I matured as a designer and leader, forged lifelong relationships, and witnessed a platform evolve from a niche tool into a global engine for inspiration. However, I recently felt a powerful pull to challenge myself and align more closely with a mission I deeply care about. I believe healthcare and education professionals are among the most influential in the world, and I am driven to empower those who dedicate their lives to others. This desire to reconnect with both my craft and a heart-led mission is what sparked this transition. Returning to the startup world has provided the exact challenge I was seeking. From utilizing AI to enhance our efficiency and decision-making to obsessing over details for a flawless user experience. Every day is dedicated to moving with speed and intentionality, knowing we are laying the foundation for a platform that will revolutionize how physicians collaborate and learn. I am grateful for the relationships and memories forged at Pinterest and excited to see what we will accomplish at Roon. We are creating the digital home for medicine—a secure, physician-only platform where medical experts can innovate, collaborate, and share knowledge. If you are a physician looking for a dedicated community to connect with peers, I encourage you to explore what we are building. We are also growing the team! If you are a designer looking for your next big adventure, come join me at Roon. Onward! 🌱 https://lnkd.in/gUAv6JNb
Experience & Education
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Anthropic
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Publications
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Notification Volume Control and Optimization System at Pinterest
KDD '18 Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
See publicationNotifications (including emails, mobile / desktop push notifications, SMS, etc.) are very effective channels for online services to engage with users and drive user engagement metrics and other business metrics. One of the most important and challenging problems in a production notification system is to decide the right frequency for each user. In this paper, we propose a novel machine learning approach to decide notification volume for each user such that long term user engagement is…
Notifications (including emails, mobile / desktop push notifications, SMS, etc.) are very effective channels for online services to engage with users and drive user engagement metrics and other business metrics. One of the most important and challenging problems in a production notification system is to decide the right frequency for each user. In this paper, we propose a novel machine learning approach to decide notification volume for each user such that long term user engagement is optimized. We will also discuss a few practical issues and design choices we have made. The new system has been deployed to production at Pinterest in mid 2017 and significantly reduced notification volume and improved CTR of notifications and site engagement metrics compared with the previous machine learning approach.
Patents
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Optimal Selection Of Notice Recipients
Issued US 11210746
A system to select the optimal recipients for receiving a notification based on shared actions.
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Optimal Notifications
Issued US 11062401
A system to determine the optimal number of notifications, type of notifications, and optimal machine generated copy for notifications
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Ramaiah Chidambaram
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Are you a startup wanting to build a GenAI-based RAG app (production-grade) for customer support in less than a month? Here’s the step 👇 1) Start with your docs -> chunk & embed them 2) Store in a vector DB (Pinecone/Weaviate) 3) Retrieve the most relevant chunks -> feed into an LLM 4) Add citations + safety filters -> deploy as an assistant The best part... With AWS Bedrock’s serverless Knowledge Base, you can skip a lot of infra headaches. Managed RAG Pipeline and enterprise-grade security. Check the architecture below 👇 Perfect for startups that want to move fast + safe. Build lean, validate with real users, and scale confidently. ✨ That’s how you ship GenAI-powered customer support in weeks, not months. You have a chance to get funding from AWS to build your PoC if you have a DPIIT certification and a valid use case, as per their policy. DM me if you’d like to benefit from this, and I’ll connect you with the concerned person.
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Sudarshan S.
Plaid • 2K followers
Really excited for Plaid’s Effects. AI is rapidly raising the bar for financial products. The next generation of experiences will be proactive, personalized, and much better at understanding what’s actually happening in a user’s financial life. That shift is what I’m most excited to talk about: how better data, models, and infrastructure are turning connected finance into intelligent finance. If you care about where fraud, payments, lending, and AI are headed next, join us at Effects. https://lnkd.in/gdYdAZaH
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2 Comments -
William Kilmer
GALLOS Technologies • 8K followers
This session we did two weeks ago was a Masterclass in bringing highly informed CISOs to discuss pressing topics in security and resilience. Well run by Gaven Smith CB and Chris Martin. Particularly interesting to me was the discussion on enforcement and incentives for securing organizations--it was a shame regulators weren't in the room taking notes!
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Dave Goldblatt
Vibe Capital • 2K followers
New Dave's Quick Hits is up. Three stories with the same flaw. 1️⃣ Vitalik Buterin on why smart people justify terrible decisions with brilliant-sounding arguments. His test: if a scam could use the exact same reasoning, the argument tells you nothing. "Responsible acceleration" fails this test. So does "inevitable transformation." 2️⃣ OpenAI led a $15M seed into Red Queen Bio to evaluate whether AI bio capabilities are matched by adequate defenses. The structure: OpenAI builds the capabilities, funds the evaluator, and the evaluator judges if OpenAI is safe. That's like letting the developer inspect their own building. 3️⃣ A method to test 100 samples of a father's DNA before making an embryo. Cost: $20,000 (same as IVF today). Result: your daughter moves from 50th percentile to 90th for traits genes control. The argument that follows: "It's irresponsible not to optimize your child." The pattern: arguments that sound sophisticated but rule nothing out. They work equally well for a legitimate company, a scam, or the opposite strategy. Vitalik's test: would this feel safe if your enemy ran it instead of someone you respect? Rules only hold when they're set before capital shows up. After that, revenue bends every line. Full analysis: https://lnkd.in/gkKk-W2F #AI #Biotech #VentureCapital #Innovation #vibecap #vibecapital
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Ritvik Pandey
Pulse • 15K followers
The XLSX format is not built for document extraction. Spreadsheets are not just glorified tables - what's just as important is the structure, formatting, relationships, and formulas that cascade across sheets. At Pulse, we trained a new spreadsheet encoder that teaches LLMs to understand large Excel files from the ground up. Not just cell contents, but the architecture. How conditional formatting triggers, where pivot tables pull their ranges, and why merged cells break everything. The result was reflected in our latest launch, Pulse Meridian: when our system processes a financial PDF, it doesn't just extract numbers, it reconstructs the spreadsheet logic: • Headers that span properly across complex table structures • Formulas that reference the right cells automatically This novel approach is reflected inside the Pulse API - the result is being able to fundamentally speak Excel. Feel free to try it now, and email us with your most complex spreadsheets!
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Jerry Liu
LlamaIndex • 45K followers
Parsing PDFs at scale with LLMs is cost prohibitive. Newer models (e.g. gemini 3) are good at reading pdfs, but you burn unnecessary vision tokens even when the page is text heavy. We’ve built in a “cost-optimizer” within LlamaParse that will dynamically route pages to fast/cheap parsing depending on its complexity. Complex pages (e.g. those with tables/charts/diagrams) will still get routed to our VLM-enabled modes. This will let you save anywhere from 50-90% of parsing costs, at much higher accuracy compared to the comparable mode of feeding screenshots into VLMs. Check it out! https://lnkd.in/g9Wpqn7w
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Yaniv F.
Flag Capital • 25K followers
This is very true. The valuation trap is real. But I don’t think this is a YC story. It’s a market story. We’re seeing the exact same thing here in Israel. Seed rounds at 30–40M for companies with no product, no real validation, sometimes barely a prototype. Not second-time founders. First-timers. I’ve personally seen more than 20 rounds like this just last year. This isn’t about YC “pushing” companies. The system as a whole hasn’t adapted. The cost of building collapsed. The speed of iteration exploded. But pricing logic stayed anchored in 2021. When capital doesn’t recalibrate to reality, it doesn’t just create paper risk. It creates structural fragility. Good companies get boxed into impossible expectations. They are forced to grow into valuations instead of growing into product-market fit. That’s how promising businesses die early. The tragedy isn’t overvaluation. The tragedy is killing companies that could have become durable, profitable, meaningful businesses. This isn’t a YC issue. It’s a venture industry inertia issue. And the longer it takes to adjust, the more collateral damage we’ll keep seeing.
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Eric Seufert
Heracles Media • 23K followers
Interesting blog post from Airbnb that describes how it built an Embedding-Based Retrieval (EBR) system for home searches. The search relevancy problem is relevant for any consumer platform that must sift through a large field of candidate items when scoring search results, but it's idiosyncratically complex for Airbnb given 1) inconsistent query parameters on the part of a user (eg., group size can change from one trip to another given different trip purposes) and 2) flexible filters in query construction (eg., open-ended vs. fixed date ranges). Airbnb's EBR pipeline consists of 1) generating listing embeddings, 2) training a model on those embeddings as a first pass, and 3) running an Approximate Nearest Neighbors (ANN) search to surface the best K candidates. The embeddings were generated using contrastive learning on queries with positive and negative pairs of candidate listings. Since booking a home on Airbnb often involves a multi-step process (search, click on listing, view pictures, read reviews, etc.), Airbnb could generate the negative listings from those that the user interacted with but didn't ultimately book. This differs from another common approach in contrastive learning, which is to simply use random items for the negative pairs. With the listing embeddings available, Airbnb could implement a Two Towers network model by calculating user embeddings on the fly (listing embeddings are generated with a nightly processing job). Euclidean Distance was used for similarity assessment; while dot product similarity performed similarly, Euclidean distance produced more uniform cluster sizes. The blog hypothesizes that this is because Euclidean distance accounts for vector magnitude, which, in this case, includes useful information such as "historical counts" (it's not clear from the post what those counts pertain to). For final retrieval, Airbnb implemented inverted file index (IVF) search. Clusters are pre-processed, and IVF requires storing only the clusters' centroids and the listings' indices, resulting in lower latency than other search methods. The EBR system captures more context from the search query when retrieving candidate listings. Airbnb notes in the blog post that its EBR system resulted in "a statistically-significant gain in overall bookings" when A/B tested against the legacy system. Blog post linked below.
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Ali Rohde
Outset Capital • 21K followers
I’m gonna hold your hand as I say this: Stop using Claude Cowork. If you’re serious about getting good at AI workflows, it’s the wrong place to spend time. Many of my incredibly sharp friends are defaulting to Claude Cowork because they think it’s the best fit for non-developers. It’s not. They’re trading real power for a small amount of convenience. That's because Claude Cowork is optimized for completing tasks. Claude Code is optimized for building systems you can reuse, extend, and share. And most importantly, the most powerful new capabilities show up in developer environments first. Tool use, memory, agents that operate across systems. That all lands in Claude Code before it trickles down anywhere else. Anthropic is doing a great job with Claude Cowork, and it will keep getting better. But it’s always going to lag behind Claude Code in capability and control. There’s a learning curve with Claude Code, but it’s mostly psychological. You don’t need to be an engineer. You just need to be willing to be uncomfortable for a bit. We’re in a moment where new tools are shipping constantly, and the real constraint is your time. If you’re going to invest hours getting better at this, you want it to compound. For me, that’s Claude Code. If I’m wrong, I’m curious: What does Claude Cowork unlock for power users that Claude Code doesn’t?
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121 Comments -
Amber Illig
The Council • 5K followers
Love it or hate it, being in the SF Bay Area is still one of the biggest hacks for First Builders to discover huge opportunities before anyone else. But what can you do if you’re not here? Cecilia for example moved here in 2001 and instantly joined Yahoo after feeling the palpable energy around early internet. And it’s been nonstop ever since as she later joined Amazon, Cruise, Replit, and her own breakout company GC AI. She credits a lot to the emerging tech density and optimism in the Bay Area. But she also mentions additional ways people can identify these opportunities early on: - Follow intuition around big waves - Follow your envy - Never lose curiosity - Watch the teen hackers - Talk to peers early and often (builds long term networks/insights)
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3 Comments -
Lakshmi Shankar
Together • 3K followers
8 months to $100M ARR. That’s not a growth story. That’s a platform shift. What Mukund Jha, Madhav Jha and the Emergent team have proven is simple: software creation just crossed a structural inflection point. The distance between idea and deployed product is collapsing — to natural language, across platforms, for anyone! Becoming one of the fastest-growing startups ever couldn’t have come at a better time. With India AI Impact Summit 2026 putting the country firmly on the global AI map, this moment feels symbolic — a world-class AI company, built from India, scaling at global speed. We at Together are proud to have backed Emergent from day one. This is what the early innings of a generational company look like. 🚀 #AgenticAI #NextBillionBuilders #IndiaAI
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1 Comment -
Neil Tewari
Conversion • 19K followers
Why we killed a $5M ARR product to build Conversion. Okay, we didn't kill it. I'm being dramatic. But, we still decided to focus almost all of our new product development entirely on a new product with $0 in revenue. Why? Because when it comes to real product market fit that can lead to top decile growth, there are 4 boxes you have to check: 1/ The person with the pain – They feel the problem every day. 2/ The person with the budget – They can pay for it. 3/ The person with the authority – They can sign the deal. 4/ The person who will actually use it – They have the keys to deploy. If all four are the same person, you have a rocket ship. Our old product had two or three of these at best. It made money, but every deal felt like pushing a boulder uphill. SEO specialists or freelancers didn't have the budget nor authority to get it through. Demand-gen or marketing leaders didn't feel the pain or use it. With Conversion, all four map to the same person: the modern B2B marketing leader. They feel the pain. They own the budget. They can sign. And they can log in tomorrow and start running campaigns. We also learned something critical: urgent > important. A big TAM and a real problem do not matter if the customer does not feel urgency. Conversion solves problems that block revenue today, which makes deals move fast. The result? Bigger commitments, more sophisticated customers, better feedback loops, and faster revenue growth. Thank you to Gili Raanan for this gem of a framework!
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Deen Panwer
3 followers
the days of constrained automation are ending. google just announced gemini enterprise a full agentic gui platform for business logic, workflows, and data orchestration. this isn’t a “better zapier.” it’s the start of a visual interface for reasoning systems. if this delivers, it’s easily the most important product builder launch in years the line between prompt engineering and app engineering just vanished. #google #gemini #ai #automation #builders #futureofwork #nocode #startups
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Sandeep J.
Confidential • 7K followers
My friend runs a DTC supplement brand. Clean greens powder. Was doing about $47K a month and wanted to scale faster. I said listen, you need AI automation. Full stack. They went all in. Claude API. n8n workflows. Built entire content engine scraping Reddit health threads and auto-generating blog posts. Complete revolution. Result ... Still doing $47K a month. But now their tools cost $1890/month and they spend 15 hours a week debugging webhooks. It's data-driven stagnation though. AI-powered loss with full tracking so they know exactly which automated system isn't working. Their CMO suggested they just... talk to their customers and improve the product taste. They said he doesn't understand AI led growth hacking.
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Brandon Li
Power • 12K followers
ctac just dropped some solid results (see below) they connected underserved communities with research over 18 months and launched 20+ trials reaching 4,600+ participants (mckinsey helped with the project management) the headline stat everyone's sharing? "50% of trials happen in just 2% of zip codes" honestly that feels a bit misleading... of course academic medical centers concentrate trials, that's where the research infrastructure actually exists. the real question isn't about zip codes, it's about getting viable sites up and running in underserved areas what actually worked: site readiness assessments (no more "we'll figure it out later") mentorship between experienced sites and newcomers platforms that actually connect sponsors with trial-ready locations but honestly? building research infrastructure shouldn't feel revolutionary in 2025 at power we see the same thing... remove the friction and suddenly patients who've been invisible to the system start enrolling. turns out people want access to cutting-edge treatments regardless of their zip code (shocking, i know)the future of medicine literally depends on everyone being able to participate, not just people who live near academic medical centers what's your take - is geography still the biggest barrier or have we moved past that?
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Daniele Bernardi
Toolhouse • 7K followers
AI ROI is being mispriced. Everyone is counting prompts, seats, token costs. The real bill is org design. - AI that saves minutes changes nothing - AI that removes handoffs changes headcount math - AI that works only with consultants is still services, not software We’re watching the same mistake as early SaaS. People are buying tools. The winners will buy labor redesign.
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Jeremiah Owyang
Blitzscaling Ventures • 40K followers
We, at Blitzscaling Ventures have invested in Ambiguous: AI agent teammates for business. Are they 1) AI agents helping my business, or 2) are they remote humans? We can't tell, it's Ambiguous! Today’s work tools assume either humans do the work, or AI replaces it. Ambiguous takes a different approach: AI coworkers that operate alongside humans in the same workspace, with real identities (each with Google accounts), shared context, and a full audit trail. Humans and AI collaborate on the same threads across Google Workspace, Slack, and more, making work feel less like automation and more like teamwork. The product is designed around product-led growth and virality (key to our investment thesis): AI coworkers naturally interact with other humans, spreading through shared threads, emails, and workflows. As teams add more coworkers and expand use cases, the platform compounds in value, moving from individual productivity to team operations and eventually enterprise-wide adoption. The founding team Ryan Waliany, Philip Lee, Dan Hsiao all worked together at a prior company Doorstead, brings a rare combination of deep technical skill and operating experience. We met the Ambiguous team through the a16z speedrun and were immediately impressed by their clarity of thought and ambition. We believe Ambiguous is defining a new category: not just AI assistants, but true AI coworkers that work like real teammates. We’re excited to partner with the team as they build the operating system for agentic work.
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Ian Livingstone
Keycard • 4K followers
Incredibly excited to announce our acquisition of Runebook (acq. by Keycard), and to share more about the work we’re already doing with customers to deploy production-ready MCP agents and tools into production. When we met with Peter Cho and Matte Noble earlier this year at MCP Night, it was immediately clear they were thinking about the future of computing in a special way. Like us, they saw MCP as the fulcrum for bringing the advances of LLMs into the systems that power modern life, but also understood that it was too difficult to adopt and challenging to secure. So when the opportunity came to bring them into the fold, it was an easy decision. They’ve been working to make MCP easier to adopt, and with their experience building beloved developer ecosystems at Heroku and Sentry, they’ll expand the work we’re already doing to let developers build trusted agentic applications in minutes — not days or weeks. You can’t become agent-native without enabling your developers to build, your employees to adopt, and your security teams to govern with full observability and policy enforcement out of the box. We’re helping customers do exactly that today. More in the blog post, linked in the comments below 👇
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Varun Anand
Clay • 52K followers
We just did a big analysis of Clay's 10,000 monthly support tickets. If you're running a support team, here's what you need to know: A few weeks ago, George Dilthey (Head of Support), went to Karan Parekh with a problem, "Hey, the org is growing really fast. We're hiring all these support people, but they still feel underwater. Help me figure out what's going on." The obvious answer? Hire more people. But candidly, we hadn't really studied the data yet. The thing we needed to know first was, how are we getting through ticket volumes? When are they coming in? What time of the day? From what geography? Then once we had that data, we had to go back to first principles: What is the actual point of support? Of course, I want to give our customers an excellent experience. I want it to be world-class. I want it to solve their problem quickly and expediently. But how would you define expediently? Is it zero wait-times? 10 minutes? 60 minutes? In this video, Karan and I break down: - The bimodal curve we discovered -- tickets aren't flat, there's a pattern you can plan for - Why Thursday-Friday have half the volume of Monday-Wednesday (and what we do with that capacity) - How to staff for sub-1 hour response times without having people idle most of the day - Our weekend coverage strategy (that doesn't burn people out and eliminates the Monday morning queue) - What our support team actually does during low-volume periods If your support team feels underwater, watch below 👇 PS I don't know why the team chose a thumbnail where my eyes are closed 🙈
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Arteen Arabshahi
Fika Ventures • 9K followers
SF AI-Native Operator Takeaway #2: In AI-native PLG, the hard part isn’t conversion... it’s discovery. Many AI-native teams are still talking about PLG using a classic SaaS mental model, but based on operator conversations in SF, that model is starting to break down in fairly obvious ways. The biggest bottleneck right now isn’t conversion. It’s discovery. In traditional PLG, users generally understood the category before they ever signed up. The problem was obvious, the product’s value was legible from the homepage, and the “aha” moment tended to show up quickly in first use. In that world, PLG meant optimizing onboarding, reducing friction, and improving free-to-paid conversion because user intent already existed. AI changes that assumption. In AI-native products, users are often curious but unclear. They don’t yet know what’s possible, value depends heavily on workflow, context, data, and role, and the product can feel abstract until it’s applied directly to their job. As a result, many users stall not because the product isn’t valuable, but because they haven’t discovered how it fits into their world and how they can't live without it. This is the real distinction people kept coming back to. PLG conversion answers, “Is this worth paying for?” PLG discovery answers, “What problem does this solve for me, right now?” What’s working best in practice is less about funnel polish and more about clarity up front: role- or workflow-specific entry points, guided examples instead of blank states, and opinionated first actions that show users a concrete outcome before asking them to explore. This also explains a broader pattern across AI-native companies. Forward-deployed teams and services-heavy delivery aren’t just implementation tools; they’re discovery mechanisms. They translate abstract AI capability into concrete workflow value, observe real use cases users wouldn’t self-discover, and feed those learnings back into what eventually becomes productized. PLG isn’t going away, but in AI-native companies it’s being redefined. Self-serve no longer means self-explanatory. Education becomes part of the product, and discovery has to come before optimization. The teams making progress aren’t obsessing over conversion rates yet. They’re focused on whether users see themselves in the product, how quickly they reach a meaningful outcome, and whether the product helps users get to a meaningful outcome for themselves quickly, without too much guesswork. Bottom line: in AI, PLG is less about removing conversion friction early and much more about creating understanding first. Once they understand, they may be hooked. Tomorrow is my last SF AI operator takeaway focusing on everyone's favorite topic du jour: 996 work schedules.
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